Artificial Intelligence-Enhanced Assessment of Lipid Profiles in Commercial Infant Foods in the United States.

Clement G Yedjou, Kevine Makoudjou, Monica Ochapa, Jinwei Liu, Samia Messeha, Paul B Tchounwou

Abstract read

In one paragraph

Article in Journal of nutrition & food sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Clement G YedjouDepartment of Biological Sciences, College of Science and Technology, Florida Agricultural and Mechanical University, 1610 S. Martin Luther King Blvd, Tallahassee, FL 32307, USA.

Kevine MakoudjouDepartment of Biological Sciences, College of Science and Technology, Florida Agricultural and Mechanical University, 1610 S. Martin Luther King Blvd, Tallahassee, FL 32307, USA.

Monica OchapaSchool of Community Health and Policy, Morgan State University, 4530 Portage Avenue Campus Near, E. Cold Spring Lane, Baltimore, MD 21251, USA.

Jinwei LiuDepartment of Computer and Information Sciences, College of Science and Technology, Florida Agricultural and Mechanical University, 1610 S. Martin Luther King Blvd, Tallahassee, FL 32307, USA.

Samia MessehaDepartment of Biological Sciences, College of Science and Technology, Florida Agricultural and Mechanical University, 1610 S. Martin Luther King Blvd, Tallahassee, FL 32307, USA.

Paul B TchounwouRCMI Center for Urban Health Disparities Research and Innovation, Morgan State University, 1700 E. Cold Spring Lane, Baltimore, MD 21251, USA.

Funding

Wastewater surveillance for addressing environmental health disparitiesU54MD013376 · NIMHD · MORGAN STATE UNIVERSITY · PI Paul B. Tchounwou · 2019 to 2026

$33.5M

NIMHD NIH HHS U54 MD013376

6 · The paper itself

Abstract

Introduction: Normal consumption of lipids is essential for optimal baby growth and neurological development, yet comprehensive analysis of lipid content in commercial baby foods remains limited. This study provides the first systematic, AI-enhanced assessment of lipid profiles across commercially available infant food products. Methods: A cross-sectional analysis of 245 commercial baby food products was conducted using artificial intelligence and machine learning algorithms for data processing and pattern recognition. Among the 245 commercial baby food products in the United States, 25 products have zero lipid content, while 220 products contain lipids ranging from 0.1 to 28.58 g of lipids. Products were categorized by total lipid content per 100g into four groups: Zero (0.0g), Low (≤ 1.0g), Moderate (>1.0-5.0g), and High (>5.0g). Statistical analyses included descriptive statistics and correlation analysis between ingredient profiles and lipid content. Results: Our analysis revealed that zero-lipid foods for infants comprised 10.2% of food products and were exclusively fruit-based, naturally low in fat, and suitable for early feeding, but limited in energy input. Low-lipid foods for infants accounted for the largest dataset and represented 45.3%, consisting of vegetable purées, fruit purées, and diluted fruit formulations, which reflect typical plant-based lipid profiles yet potentially require complementary higher-fat foods to meet caloric needs. The moderate-lipid food products accounted for 33.9% of the dataset. These food products included grain-vegetable mixtures, fortified fruit blends, and enriched beverages, indicating the incorporation of added oils and/or higher-fat natural ingredients to provide balanced energy.High-lipid foods such as fortified cereals, meat-based meals, and snack-type products made up 10% of the dataset. These items provide significant energy, which is especially important for infants between 6 months and 2 years old, as they have increased caloric needs relative to their size. Conclusion: Using AI and machine learning, this analysis revealed that baby foods on the market show clear variations in fat content linked to their main ingredients. Since many foods are high in fat, caregivers may need to make intentional choices to ensure infants receive adequate energy. These findings offer valuable reference points for parents, pediatric nutrition advice, and future regulatory decisions.

Indexed as

Artificial intelligenceCommercial baby foodInfant nutritionLipid contentNutritional analysis

Identifiers

PMID41878412

PMCPMC13007982

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LicenceCC BY

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.